gitlab-mcp: Skill for Claude Code

Self-Improvement Orchestrator

Autonomous loop controller for evolutionary code improvement. Manages the full lifecycle: setup, research, planning, execution, tournament selection, history recording, and stop-condition evaluation.

When to Use

• You want to iteratively improve a codebase toward a measurable benchmark goal
• Optimization tasks: performance, bundle size, test coverage, accuracy
• Code quality improvement with measurable metrics

When NOT to Use

• No measurable benchmark available
• One-shot fix or feature request → use /omg-autopilot
• Manual, interactive coding → use /ralph

Autonomous Execution Policy

NEVER stop or pause to ask the user during the improvement loop. Once the gate check passes and the loop begins, run fully autonomously until a stop condition is met.

• Do not ask for confirmation between iterations
• On agent failure: retry once, then skip and continue
• On all plans rejected: log it, continue to next iteration
• The only things that stop the loop are the stop conditions in Step 11

State Tracking

All state lives under .omc/self-improve/:

.omc/self-improve/
├── config/
│   ├── settings.json          # agents, benchmark, thresholds, sealed_files
│   ├── goal.md                # Improvement objective + target metric
│   ├── harness.md             # Guardrail rules (H001/H002/H003)
│   └── idea.md                # User experiment ideas
├── state/
│   ├── agent-settings.json    # iterations, best_score, status, counters
│   ├── iteration_state.json   # Within-iteration progress (resumability)
│   ├── research_briefs/       # Research output per round
│   ├── iteration_history/     # Full history per round
│   ├── merge_reports/         # Tournament results
│   └── plan_archive/          # Archived plans (permanent)
├── plans/                     # Active plans (current round)
└── tracking/
    ├── raw_data.json          # All candidate scores
    ├── baseline.json          # Initial benchmark score
    └── events.json            # Config changes